Mined Semantic Analysis (MSA) is a novel distributional semantics approach which employs data mining techniques. MSA embraces knowledge-driven analysis of natural languages. It uncovers implicit relations between concepts by mining for their associations in target encyclopedic corpora. MSA exploits not only target corpus content but also its knowledge graph (e.g., "See also" link graph of Wikip...

Background: Words in the Mental Lexicon (ML) construct semantic field through associative and/ or semantic connections, with a pervasive native speaker preference for the former. Non-native preferences, however, demand further inquiry. Previous studies have revealed inconsistent Lexical Access (LA) patterns due to the limitations in the methodology and response categorization. Objectives: To f...

This paper introduces a novel method for measuring semantic relatedness using semantic profiles constructed from salient encyclopedic features. The model is built on the notion that the meaning of a word can be characterized by the salient concepts found in its immediate context. In addition to being computationally efficient, the new model has superior performance and remarkable consistency wh...

abstract aim and background: the present research studied episodic and semantic memory in quran memories and non- quran memories among girl students. methods and materials: research design was based on semi-experimental design. this study included 180 quran memories, beginner and non quran memories among girl students in 3 educational grades: primary, secondary and high school were chosen by cl...

With the rapid growth of data generated by social web applications new paradigms in the generation of knowledge are opening. This paper introduces Crowd Explicit Sentiment Analysis (CESA) as an approach for sentiment analysis in social media environments. Similar to Explicit Semantic Analysis, microblog posts are indexed by a predefined collection of documents. In CESA, these documents are buil...

This study examines the relationship between two kinds of semantic spaces — i.e., spaces based on term frequency (tf) and word cooccurrence frequency (co) — and four semantic relations — i.e., synonymy, coordination, superordination, and collocation — by comparing, for each semantic relation, the performance of two semantic spaces in predicting word association. The simulation experiment demons...

Web applications increasingly utilize search techniques that heavily rely on content-based text and image analyses. For example, for parental site filtering, it is necessary to identify adult sites. These applications must rely on a semantic analysis of images in the process of identification where text analysis alone is insufficient. In this article, we describe our site filtering system "WebG...